Fire (Dec 2023)

Modeling the Monthly Distribution of MODIS Active Fire Detections from a Satellite-Derived Fuel Dryness Index by Vegetation Type and Ecoregion in Mexico

  • Daniel José Vega-Nieva,
  • María Guadalupe Nava-Miranda,
  • Jaime Briseño-Reyes,
  • Pablito Marcelo López-Serrano,
  • José Javier Corral-Rivas,
  • María Isabel Cruz-López,
  • Martin Cuahutle,
  • Rainer Ressl,
  • Ernesto Alvarado-Celestino,
  • Robert E. Burgan

DOI
https://doi.org/10.3390/fire7010011
Journal volume & issue
Vol. 7, no. 1
p. 11

Abstract

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The knowledge of the effects of fuel dryness on fire occurrence is critical for sound forest fire management planning, particularly in a changing climate. This study aimed to analyze the monthly distributions of MODIS active fire (AF) detections and their relationships with a fuel dryness index (FDI) based on satellite-derived weather and vegetation greenness. Monthly AF distributions showed unimodal distributions against FDI, which were described using generalized Weibull equations, fitting a total of 19 vegetation types and ecoregions analyzed in Mexico. Monthly peaks of fire activity occurred at lower FDI values (wetter fuels) in more hygrophytic ecosystems and ecoregions, such as wet tropical forests, compared to higher fire activity in higher FDI values (drier fuels) for the more arid ecosystems, such as desert shrublands. In addition, the range of fuel dryness at which most monthly fire activity occurred was wider for wetter vegetation types and regions compared to a narrower range of fuel dryness for higher monthly fire occurrence in the more arid vegetation types and ecoregions. The results from the current study contribute towards improving our understanding of the relationships between fuel dryness and fire occurrence in a variety of vegetation types and regions in Mexico.

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